LAPSE:2023.29536
Published Article

LAPSE:2023.29536
A Modified Niching Crow Search Approach to Well Placement Optimization
April 13, 2023
Abstract
Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.
Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.
Record ID
Keywords
crow search algorithm, multimodal optimization, niching crow search algorithm, non-convex, well placement optimization
Subject
Suggested Citation
Islam J, Rahaman MSA, Vasant PM, Negash BM, Hoqe A, Khalifa Alhitmi H, Watada J. A Modified Niching Crow Search Approach to Well Placement Optimization. (2023). LAPSE:2023.29536
Author Affiliations
Islam J: Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Rahaman MSA: Shale Gas Research Group, Institute of Hydrocarbon Recovery, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia [ORCID]
Vasant PM: Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia [ORCID]
Negash BM: Petroleum Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Hoqe A: Electrical & Electronic Engineering Department, Chittagong University of Engineering and Technology, Chittagong 4349, Bangladesh
Khalifa Alhitmi H: College of Business and Economics, Qatar University, Doha 00974, Qatar
Watada J: Department of Computer & Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia
Rahaman MSA: Shale Gas Research Group, Institute of Hydrocarbon Recovery, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia [ORCID]
Vasant PM: Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia [ORCID]
Negash BM: Petroleum Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Hoqe A: Electrical & Electronic Engineering Department, Chittagong University of Engineering and Technology, Chittagong 4349, Bangladesh
Khalifa Alhitmi H: College of Business and Economics, Qatar University, Doha 00974, Qatar
Watada J: Department of Computer & Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia
Journal Name
Energies
Volume
14
Issue
4
First Page
857
Year
2021
Publication Date
2021-02-06
ISSN
1996-1073
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Original Submission
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PII: en14040857, Publication Type: Journal Article
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LAPSE:2023.29536
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https://doi.org/10.3390/en14040857
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Apr 13, 2023
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